Dynamic inspection method and device for inspection business data based on data warehouse

Abstract

The invention relates to an inspection business data dynamic inspection method and device based on a data warehouse, and the method comprises the steps: obtaining a query queue formed by a plurality of business data query tasks, and for each piece of business data, the business data is data obtained for an inspection task of a pipeline; according to the data type of the data stored in the data warehouse, a plurality of parallel queues are established in the cache, and data of one data type in the data warehouse is cached in each parallel queue; according to the data type of each piece of business data in the query queue, determining a target parallel queue corresponding to each piece of business data from a plurality of parallel queues so as to process query tasks corresponding to the corresponding business data in parallel through the determined target parallel queues to obtain query results corresponding to each query task, and carrying out dynamic check according to a query result. By means of the method, the data stored in the data warehouse is decomposed into the multiple parallel queues which are dynamically created, and the processing efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of pipeline network inspection, and in particular to a method and device for dynamically checking inspection business data based on a data warehouse. Background Art

[0002] Oil and gas pipeline inspection is an important safety guarantee measure for the production and operation of the petroleum system. The inspection work is completed on schedule according to the pre-established inspection plan. The inspection content includes investigating whether there are abnormal conditions such as oil and gas leaks, wandering personnel, oil theft, etc. in the pipeline.

[0003] Pipeline inspection is a procedural process. Problems found during the inspection need to be fed back to the management and control system in a timely manner. However, for inspection data of a large magnitude, if you want to query the inspection data of multiple pipelines stored in the data warehouse in real time, or perform dynamic inspections on each pipeline in real time, the query and processing of the inspection data will directly affect the processing speed due to the large amount of data stored in the data warehouse. Summary of the invention

[0004] The technical problem to be solved by the present invention is to provide a method and device for dynamic inspection of inspection business data based on a data warehouse, aiming to solve at least one of the above technical problems.

[0005] In the first aspect, the technical solution of the present invention to solve the above technical problem is as follows: a method for dynamic inspection of patrol business data based on a data warehouse, the method comprising:

[0006] A query queue formed by query tasks for obtaining multiple business data, for each of the business data, the business data is data obtained by an inspection task for a pipeline;

[0007] According to the data type of the data stored in the data warehouse, a plurality of parallel queues are established in the cache, each parallel queue caches data of a data type in the data warehouse;

[0008] According to the data type of each business data in the query queue, the target parallel queue corresponding to each business data is determined from the multiple parallel queues, so that the query tasks corresponding to the corresponding business data are processed in parallel through the determined target parallel queues to obtain the query results corresponding to each query task, and dynamic checks are performed based on the query results.

[0009] The beneficial effect of the present invention is that the present invention decomposes the data stored in the data warehouse into multiple dynamically created parallel queues for processing, thereby improving the query speed when querying the inspection data of a certain pipeline, and improving the processing efficiency when performing dynamic inspection based on the query results.

[0010] Based on the above technical solution, the present invention can also be improved as follows.

[0011] Furthermore, for each query result corresponding to the query task, the method further includes:

[0012] Providing a plurality of display modes to the user through a display mode selection page, wherein the display modes include at least two of a list, a group, a cross table, a column chart, a bar chart, a pie chart, an area chart, a combination chart, a dashboard, and a map;

[0013] In response to the user's selection operation on a target display mode among multiple display modes, the query result is displayed in the target display mode.

[0014] The beneficial effect of adopting the above further solution is that the query results can be displayed in different display modes to meet different display requirements.

[0015] Furthermore, the data stored in the above data warehouse is stored through different server nodes, and the method further includes:

[0016] For each of the server nodes, obtaining node status and resource load information corresponding to the server node;

[0017] Determining whether the node states corresponding to the server nodes are the same, and if the node states corresponding to the server nodes are the same, determining the target route according to the resource load information of the server nodes;

[0018] If the node states corresponding to the server nodes are different, determining the target route according to the node states of the server nodes;

[0019] The data stored in the data warehouse is obtained through the target route.

[0020] The beneficial effect of adopting the above further scheme is that it mainly takes the business type from the software perspective, supplemented by the resource load information from the hardware perspective, and uses a combination of software and hardware information to perform dynamic load balancing, thereby avoiding excessive load on a single server node and maximizing the use of resources of each storage server node.

[0021] Furthermore, for each of the server nodes, the node status is status information corresponding to the server node when processing different types of services, including breakpoint resume status, data synchronization status, and failover status.

[0022] The beneficial effect of adopting the above further solution is that the stability of each storage server node can be further improved by considering the status information corresponding to different types of services, that is, the impact of different services on load balancing.

[0023] Furthermore, for each of the server nodes, the resource load information includes CPU occupancy, memory occupancy, and disk IO occupancy.

[0024] The beneficial effect of adopting the above further solution is that, taking into account different resource load information, the stability of each storage server node can be further improved.

[0025] Further, the data stored in the data warehouse includes inspection data of multiple pipelines, and for each of the pipelines, the inspection data includes operation data corresponding to each checkpoint in the pipeline, and the query result is the inspection data of the target pipeline in the multiple pipelines, and the dynamic inspection according to the query result includes:

[0026] According to the inspection data corresponding to the target pipeline, a risk assessment is performed on the target pipeline to obtain a risk assessment result.

[0027] The beneficial effect of adopting the above further solution is that, based on the query results, the risk assessment of the target pipeline can be accurately performed.

[0028] Furthermore, the inspection data includes temperature, noise, vibration value, wall thickness and concentration of gas in the pipeline.

[0029] The beneficial effect of adopting the above further solution is that, based on different types of inspection data, a comprehensive risk assessment of the target pipeline can be performed.

[0030] In a second aspect, in order to solve the above technical problems, the present invention also provides a dynamic inspection device for patrol business data based on a data warehouse, the device comprising:

[0031] An acquisition module, used for acquiring a query queue formed by query tasks for multiple business data, wherein for each of the business data, the business data is data obtained by an inspection task for a pipeline;

[0032] A parallel queue establishment module is used to establish multiple parallel queues in the cache according to the data type of the data stored in the data warehouse, each parallel queue caches data of a data type in the data warehouse;

[0033] A dynamic inspection module is used to determine the target parallel queue corresponding to each business data from multiple parallel queues according to the data type of each business data in the query queue, so as to parallelly process the query tasks corresponding to the corresponding business data through the determined target parallel queues, obtain the query results corresponding to each query task, and perform dynamic inspection based on the query results.

[0034] In the third aspect, in order to solve the above-mentioned technical problems, the present invention also provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the dynamic inspection method of patrol business data based on the data warehouse of the present application is implemented.

[0035] In a fourth aspect, in order to solve the above-mentioned technical problem, the present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the data warehouse-based inspection business data dynamic inspection method of the present application is implemented.

[0036] Additional aspects and advantages of the present application will be partially given in the following description, which will become apparent from the following description, or will be understood through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for describing the embodiments of the present invention are briefly introduced below.

[0038] Figure 1 A flowchart of a method for dynamically checking patrol business data based on a data warehouse provided by an embodiment of the present invention;

[0039] Figure 2 A schematic diagram of the structure of a data warehouse-based dynamic inspection device for inspection service data provided by an embodiment of the present invention;

[0040] Figure 3 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0041] The principles and features of the present invention are described below. The examples given are only used to explain the present invention and are not used to limit the scope of the present invention.

[0042] The technical solution of the present invention and how the technical solution of the present invention solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present invention will be described below in conjunction with the accompanying drawings.

[0043] The solution provided by the embodiment of the present invention can be applied to any application scenario where dynamic inspection of pipeline inspection data is required. The solution provided by the embodiment of the present invention can be executed by any electronic device, for example, it can be a user's terminal device, including at least one of the following: a smart phone, a tablet computer, a laptop computer, a desktop computer, a smart speaker, a smart watch, a smart TV, and a smart car device.

[0044] The embodiment of the present invention provides a possible implementation method, such as Figure 1 As shown, a flowchart of a method for dynamic inspection of patrol business data based on a data warehouse is provided. The scheme can be executed by any electronic device, for example, a terminal device, or jointly executed by a terminal device and a server. For the convenience of description, the method provided by the embodiment of the present invention will be described below by taking the terminal device as the execution subject as an example. Figure 1 The method may include the following steps:

[0045] S110, obtaining a query queue formed by query tasks of multiple business data, for each business data, the business data is data obtained by an inspection task for a pipeline;

[0046] S120, establishing a plurality of parallel queues in a cache according to the data type of the data stored in the data warehouse, wherein each parallel queue caches data of a data type in the data warehouse;

[0047] S130, according to the data type of each business data in the query queue, determine the target parallel queue corresponding to each business data from the multiple parallel queues, so as to parallelly process the query tasks corresponding to the corresponding business data through the determined target parallel queues, obtain the query results corresponding to each query task, and perform dynamic inspection based on the query results.

[0048] Through the method of the present invention, the data stored in the data warehouse is decomposed into multiple dynamically created parallel queues for processing, so that when querying the inspection data of a certain pipeline, the query speed is improved, and when dynamic inspection is performed based on the query results, the processing efficiency is improved.

[0049] The solution of the present invention is further described below in conjunction with the following specific embodiments. In this embodiment, the method for dynamically checking patrol service data based on a data warehouse may include the following steps:

[0050] S110, obtaining a query queue formed by query tasks of multiple business data, for each business data, the business data is data obtained by an inspection task for a pipeline;

[0051] The query task of multiple business data may be initiated by one user or by multiple users, that is, one user may initiate at least one query task, and one query task corresponds to the business data corresponding to one pipeline.

[0052] S120, establishing a plurality of parallel queues in a cache according to the data type of the data stored in the data warehouse, wherein each parallel queue caches data of a data type in the data warehouse;

[0053] Among them, the specific role of the parallel queue is: through the mq middleware service to establish multiple parallel queues in the cache, the data in the data warehouse is decomposed into multiple dynamically created parallel queues for processing.

[0054] Among them, the data stored in the data warehouse can be stored according to different data types, and each data type refers to each type of inspection data corresponding to the pipeline. Optionally, for example, the inspection data includes temperature, noise, vibration value, wall thickness and concentration of the gas located in the pipeline. The temperature corresponding to each pipeline can be stored in a parallel queue, and the noise corresponding to each pipeline can be stored in another parallel queue. And so on. Multiple parallel queues can be established to store different types of inspection data.

[0055] This solution creates multiple parallel queues, and the parallel queues are built in the cache. For example, if there are 200 parallel queues, the data in the data warehouse will be decomposed into 200 parallel queues. This can achieve the acquisition and analysis of a large amount of data with a smaller memory, reduce the amount of data in a single node, and improve the query speed.

[0056] S130, according to the data type of each business data in the query queue, determine the target parallel queue corresponding to each business data from the multiple parallel queues, so as to parallelly process the query tasks corresponding to the corresponding business data through the determined target parallel queues, obtain the query results corresponding to each query task, and perform dynamic inspection based on the query results.

[0057] The target parallel queue may be at least one of the established multiple parallel queues, and the corresponding query result may be at least one type of data in the inspection data.

[0058] Optionally, before caching the data in the data warehouse into each parallel queue, the method further includes:

[0059] Data in the data warehouse is cleaned and the cleaned data is cached in various parallel queues. Data cleaning includes missing value processing, outlier processing, and deduplication processing. Missing value processing can be to delete the missing value or fill the missing value with the mean. Specifically, the data is divided into several groups according to the attribute with the largest correlation coefficient with the missing value attribute (such as year, region, etc.), and then the mean of each group is calculated separately, and the missing data is replaced with these means. The judgment of outliers can be clustered, and the outliers are replaced by the mean. Normalized data can realize automatic collection, editing, and normalization according to conditions, reduce the hardware cost and time cost of obtaining large amounts of information, and improve efficiency.

[0060] Optionally, the present solution also includes: analyzing the data in the data warehouse by cross analysis, and caching the analyzed data in each parallel queue, wherein the cross analysis refers to cross processing any two variables in a one-dimensional single table to form a cross table.

[0061] Optionally, for each query result corresponding to the query task, the method further includes:

[0062] Providing a plurality of display modes to the user through a display mode selection page, wherein the display modes include at least two of a list, a group, a cross table, a column chart, a bar chart, a pie chart, an area chart, a combination chart, a dashboard, and a map;

[0063] In response to the user's selection operation on a target display mode among multiple display modes, the query result is displayed in the target display mode.

[0064] Optionally, the data stored in the data warehouse is stored via different server nodes, and the method further includes:

[0065] For each of the server nodes, obtaining node status and resource load information corresponding to the server node;

[0066] Determining whether the node states corresponding to the server nodes are the same, and if the node states corresponding to the server nodes are the same, determining the target route according to the resource load information of the server nodes;

[0067] If the node states corresponding to the server nodes are different, determining the target route according to the node states of the server nodes;

[0068] The data stored in the data warehouse is obtained through the target route.

[0069] Based on the business type from the software perspective and supplemented by the resource load information from the hardware perspective, dynamic load balancing is performed by combining software and hardware information to avoid excessive load on a single server node and maximize the use of resources on each storage server node.

[0070] Optionally, for each of the server nodes, the node status is status information corresponding to the server node when processing different types of services, including breakpoint resume status, data synchronization status, and failover status.

[0071] Optionally, for each of the server nodes, the resource load information includes CPU occupancy, memory occupancy, and disk IO occupancy.

[0072] Among them, the node status is the status information corresponding to the server node when processing different types of services, and in this embodiment includes breakpoint resume status, data synchronization status and failover status. Since the services running at different times may be different at the server node, resulting in different loads at different times, three node states corresponding to the three services of breakpoint resume, data synchronization and failover are set in this embodiment. Breakpoint resume means that when downloading or uploading, the download or upload task is artificially divided into several parts, and each part uses a thread to upload or download. If a network failure occurs, the unfinished part of the upload or download can be continued from the part that has been uploaded or downloaded; data synchronization refers to keeping the data on the storage server node synchronized with the historical data; failover refers to quickly enabling redundant or backup servers, systems, hardware or networks to take over their work when an active service or application is terminated unexpectedly.

[0073] In addition, this embodiment includes but is not limited to the above three node states. Corresponding node states can also be set according to other business settings such as storing real-time data, which will not be enumerated here one by one.

[0074] In this embodiment, based on the importance of the three services of breakpoint resume, data synchronization and failover in practical applications, corresponding preset node status priorities can also be configured, including: breakpoint resume status is the first priority, which is the highest priority; data synchronization status is the second priority; failover status is the third priority, which is the lowest priority. The target route can be determined according to the order of the preset node status priorities from high to low.

[0075] Specifically, in the process of determining whether the node states corresponding to the server nodes are the same, first determine whether the breakpoint resume states are the same according to the priority. If they are the same, then determine whether the data synchronization states are the same. If they are the same, finally determine whether the failover states are the same.

[0076] Optionally, if the node states corresponding to the server nodes are the same, one implementation method of determining the target route according to the resource load information of the server nodes is:

[0077] According to the resource load information of each of the server nodes, the load score of each server node is determined, and the target route is determined according to each load score. More specifically, the CPU occupancy rate, memory occupancy rate and disk IO occupancy rate can be weighted and summed based on preset weights, and the summation result is used as the load score.

[0078] For each server node, the larger the load score of the server node is, the worse the load capacity is, the lower the possibility of selecting the server node is, and the lower the possibility of using the server node as the target route is.

[0079] Optionally, the data stored in the data warehouse includes inspection data of multiple pipelines, and for each of the pipelines, the inspection data includes operation data corresponding to each checkpoint in the pipeline, and the query result is the inspection data of a target pipeline among the multiple pipelines, and the dynamic inspection according to the query result includes:

[0080] According to the inspection data corresponding to the target pipeline, a risk assessment is performed on the target pipeline to obtain a risk assessment result.

[0081] Optionally, the inspection data includes temperature, noise, vibration value, wall thickness and concentration of gas in the pipeline.

[0082] Optionally, a possible implementation method of performing risk assessment on the target pipeline according to the inspection data corresponding to the target pipeline to obtain the risk assessment result is:

[0083] According to the inspection data corresponding to the target pipeline, a model established by a machine learning method is used to perform risk assessment on the target pipeline to obtain a risk assessment result. In the process of obtaining the risk assessment result, the inspection data corresponding to the target pipeline can be firstly subjected to data standardization processing, and the formula is: Ni = (x i -X1orX0) / (X1-X0), where Ni is the i-th data standardization strategy index, X1 is the maximum value of the safety range of the inspection data, X0 is the minimum value of the safety range of the inspection data, and X1orX0 means that X1 and X0 are closest to x i The value of N i is imported into the pre-established impact model formula to obtain the risk value Y n ; the impact model formula is:

[0084]

[0085] Wherein, Ai is the ith risk factor, Yn is the risk value, and Ni is the ith data normalization strategy index. Each of the parameters of temperature, noise, vibration value, wall thickness, and concentration of the gas in the pipeline may be a risk factor.

[0086] After the risk value is determined, the risk value can be compared with the risk threshold. When the risk value is greater than the risk threshold, a risk alarm can be issued.

[0087] Based on Figure 1 Based on the same principle as the method shown in , the embodiment of the present invention also provides a dynamic inspection device 20 for patrol service data based on a data warehouse, such as Figure 2 As shown in , the data warehouse-based patrol service data dynamic inspection device 20 may include an acquisition module 210, a parallel queue establishment module 220 and a dynamic inspection module 230, wherein:

[0088] An acquisition module 210 is used to acquire a query queue formed by query tasks of multiple business data, and for each of the business data, the business data is data obtained by an inspection task for a pipeline;

[0089] A parallel queue establishment module 220 is used to establish multiple parallel queues in the cache according to the data type of the data stored in the data warehouse, each parallel queue caches data of a data type in the data warehouse;

[0090] The dynamic inspection module 230 is used to determine the target parallel queue corresponding to each business data from the multiple parallel queues according to the data type of each business data in the query queue, so as to parallelly process the query tasks corresponding to the corresponding business data through the determined target parallel queues, obtain the query results corresponding to each query task, and perform dynamic inspection based on the query results.

[0091] Optionally, for each query result corresponding to the query task, the device further includes:

[0092] A display module, used to provide a plurality of display modes to the user through a display mode selection page, wherein the display modes include at least two of a list, a group, a cross table, a column chart, a bar chart, a pie chart, an area chart, a combination chart, a dashboard and a map;

[0093] In response to the user's selection operation on a target display mode among multiple display modes, the query result is displayed in the target display mode.

[0094] Optionally, the data stored in the above data warehouse is stored through different server nodes, and the device further includes:

[0095] The target route determination module is used to obtain the node status and resource load information corresponding to each server node for each server node; determine whether the node status corresponding to each server node is the same, and if so, determine the target route according to the resource load information of each server node; if the node status corresponding to each server node is different, determine the target route according to the node status of each server node; and obtain the data stored in the data warehouse through the target route.

[0096] Optionally, for each of the server nodes, the node status is status information corresponding to the server node when processing different types of services, including breakpoint resume status, data synchronization status, and failover status.

[0097] Optionally, for each of the server nodes, the resource load information includes CPU occupancy, memory occupancy, and disk IO occupancy.

[0098] Optionally, the data stored in the data warehouse includes inspection data of multiple pipelines, and for each of the pipelines, the inspection data includes operation data corresponding to each inspection point in the pipeline, and the query result is the inspection data of the target pipeline in the multiple pipelines. When the dynamic inspection module 230 performs a dynamic inspection according to the query result, it is specifically used to:

[0099] According to the inspection data corresponding to the target pipeline, a risk assessment is performed on the target pipeline to obtain a risk assessment result.

[0100] Optionally, the inspection data includes temperature, noise, vibration value, wall thickness and concentration of gas in the pipeline.

[0101] The dynamic inspection device for patrol business data based on data warehouse in the embodiment of the present invention can execute the dynamic inspection method for patrol business data based on data warehouse provided by the embodiment of the present invention. The implementation principle is similar. The actions performed by each module and unit in the dynamic inspection device for patrol business data based on data warehouse in each embodiment of the present invention correspond to the steps in the dynamic inspection method for patrol business data based on data warehouse in each embodiment of the present invention. For the detailed functional description of each module of the dynamic inspection device for patrol business data based on data warehouse, please refer to the description in the corresponding dynamic inspection method for patrol business data based on data warehouse shown in the previous text, which will not be repeated here.

[0102] Among them, the above-mentioned data warehouse-based dynamic inspection device for patrol business data can be a computer program (including program code) running in a computer device, for example, the data warehouse-based dynamic inspection device for patrol business data is an application software; the device can be used to execute the corresponding steps in the method provided in an embodiment of the present invention.

[0103] In some embodiments, the dynamic inspection device for patrol business data based on a data warehouse provided in an embodiment of the present invention can be implemented in a combination of software and hardware. As an example, the dynamic inspection device for patrol business data based on a data warehouse provided in an embodiment of the present invention can be a processor in the form of a hardware decoding processor, which is programmed to execute the dynamic inspection method for patrol business data based on a data warehouse provided in an embodiment of the present invention. For example, the processor in the form of a hardware decoding processor can adopt one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), field programmable gate arrays (FPGAs) or other electronic components.

[0104] In other embodiments, the data warehouse-based inspection service data dynamic inspection device provided by the embodiment of the present invention can be implemented in software. Figure 2 A dynamic inspection device for patrol business data based on a data warehouse stored in a memory is shown, which can be software in the form of programs and plug-ins, and includes a series of modules, including an acquisition module 210, a parallel queue establishment module 220 and a dynamic inspection module 230, which are used to implement the dynamic inspection method for patrol business data based on a data warehouse provided in an embodiment of the present invention.

[0105] The modules involved in the embodiments of the present invention may be implemented by software or hardware, wherein the name of a module does not limit the module itself in some cases.

[0106] Based on the same principle as the method shown in the embodiments of the present invention, an electronic device is also provided in the embodiments of the present invention, which may include but is not limited to: a processor and a memory; the memory is used to store a computer program; the processor is used to execute the method shown in any embodiment of the present invention by calling the computer program.

[0107] In an alternative embodiment, an electronic device is provided, such as Figure 3 As shown, Figure 3 The electronic device 4000 shown includes: a processor 4001 and a memory 4003. The processor 4001 and the memory 4003 are connected, such as through a bus 4002. Optionally, the electronic device 4000 may also include a transceiver 4004, which may be used for data interaction between the electronic device and other electronic devices, such as data transmission and / or data reception. It should be noted that in actual applications, the transceiver 4004 is not limited to one, and the structure of the electronic device 4000 does not constitute a limitation on the embodiments of the present invention.

[0108] Processor 4001 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It may implement or execute various exemplary logic blocks, modules and circuits described in conjunction with the disclosure of the present invention. Processor 4001 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0109] The bus 4002 may include a path to transmit information between the above components. The bus 4002 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus 4002 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0110] The memory 4003 can be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compressed optical disk, laser disk, optical disk, digital versatile disk, Blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited to this.

[0111] The memory 4003 is used to store the application code (computer program) for executing the solution of the present invention, and the execution is controlled by the processor 4001. The processor 4001 is used to execute the application code stored in the memory 4003 to implement the content shown in the above method embodiment.

[0112] The electronic device may also be a terminal device. Figure 3 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0113] An embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored. When the computer-readable storage medium is run on a computer, the computer can execute the corresponding contents of the aforementioned method embodiment.

[0114] According to another aspect of the present invention, a computer program product or a computer program is also provided, the computer program product or the computer program comprising computer instructions, the computer instructions being stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the methods provided in the implementation modes of the above-mentioned various embodiments.

[0115] Computer program code for performing the operations of the present invention may be written in one or more programming languages, or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0116] It should be understood that the flow charts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the method and computer program product according to various embodiments of the present invention. In this regard, each box in the flow chart or block diagram can represent a module, a program segment, or a part of a code, and the module, the program segment, or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a sequence different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0117] The computer-readable storage medium provided by the embodiment of the present invention may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, device, or device.

[0118] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by the electronic device, the electronic device executes the method shown in the above embodiment.

[0119] The above description is only a preferred embodiment of the present invention and an explanation of the technical principles used. Those skilled in the art should understand that the disclosure scope involved in the present invention is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above disclosed concept. For example, the above features are replaced with the technical features with similar functions disclosed in the present invention (but not limited to) by each other.

Claims

1. A method for dynamic inspection of inspection business data based on a data warehouse, characterized in that: The following steps are involved: A query queue formed by query tasks for obtaining multiple business data, for each of the business data, the business data is data obtained by an inspection task for a pipeline; According to the data type of the data stored in the data warehouse, a plurality of parallel queues are established in the cache, each parallel queue caches data of a data type in the data warehouse; According to the data type of each business data in the query queue, the target parallel queue corresponding to each business data is determined from the multiple parallel queues, so that the query tasks corresponding to the corresponding business data are processed in parallel through the determined target parallel queues to obtain the query results corresponding to each query task, and dynamic checks are performed based on the query results.

2. The method according to claim 1, characterized in that: For each query result corresponding to the query task, the method further includes: Providing a plurality of display modes to the user through a display mode selection page, wherein the display modes include at least two of a list, a group, a cross table, a column chart, a bar chart, a pie chart, an area chart, a combination chart, a dashboard, and a map; In response to the user's selection operation on a target display mode among multiple display modes, the query result is displayed in the target display mode.

3. The method according to claim 1, characterized in that The data stored in the data warehouse is stored via different server nodes, and the method further comprises: For each of the server nodes, obtaining node status and resource load information corresponding to the server node; Determining whether the node states corresponding to the server nodes are the same, and if the node states corresponding to the server nodes are the same, determining the target route according to the resource load information of the server nodes; If the node states corresponding to the server nodes are different, determining the target route according to the node states of the server nodes; The data stored in the data warehouse is obtained through the target route.

4. The method according to claim 3, characterized in that For each of the server nodes, the node status is status information corresponding to the server node when processing different types of services, including breakpoint resume status, data synchronization status, and failover status.

5. The method according to claim 3, characterized in that: For each of the server nodes, the resource load information includes CPU occupancy, memory occupancy, and disk IO occupancy.

6. The method according to any one of claims 1 to 5, characterized in that The data stored in the data warehouse includes inspection data of multiple pipelines. For each of the pipelines, the inspection data includes operation data corresponding to each inspection point in the pipeline. The query result is the inspection data of a target pipeline among the multiple pipelines. The dynamic inspection according to the query result includes: According to the inspection data corresponding to the target pipeline, a risk assessment is performed on the target pipeline to obtain a risk assessment result.

7. The method according to claim 6, characterized in that The inspection data includes temperature, noise, vibration value, wall thickness and concentration of gas in the pipeline.

8. A dynamic inspection device for patrol business data based on a data warehouse, characterized in that: include: An acquisition module, used for acquiring a query queue formed by query tasks for multiple business data, wherein for each of the business data, the business data is data obtained by an inspection task for a pipeline; A parallel queue establishment module is used to establish multiple parallel queues in the cache according to the data type of the data stored in the data warehouse, each parallel queue caches data of a data type in the data warehouse; A dynamic inspection module is used to determine the target parallel queue corresponding to each business data from multiple parallel queues according to the data type of each business data in the query queue, so as to parallelly process the query tasks corresponding to the corresponding business data through the determined target parallel queues, obtain the query results corresponding to each query task, and perform dynamic inspection based on the query results.

9. An electronic device, characterized in that: The method comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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